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Mid-Term Review

Mid-Term Review. John W. Worley AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece http://www.wcl.ee.upatras.gr/AudioGroup/. Tasks. 2.1 The precedence effect Franssen illusion 2.2 Reliability of auditory cues in mul ti-source scenarios

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Mid-Term Review

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  1. Mid-Term Review John W. Worley AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece http://www.wcl.ee.upatras.gr/AudioGroup/

  2. Tasks • 2.1 The precedence effect • Franssen illusion • 2.2 Reliability of auditory cues in multi-source scenarios • Learning non-individualised HRTFs • 2.3 Perceptual models of room reverberation with application to speech recognition • Complex smoothed room responses • Perceptual factors in room responses

  3. Task 2.1 Franssen illusion • Reverberant environments = cue to multiple directions. • The precedence effect = stable directional percept. • Franssen illusion (F.I.) • Precedence effect. • ITD/ILD dependant

  4. Task 2.1 Franssen illusion • Hypothesis • Localisation requires transients. • Signal spectral density. • Room differences. • ITD/ILD dependant. • Solution • Various onset transitions. • Sinusoid & Harmonic complex’s. • Large vs. small rooms • At present: • F.I. in reverberation chamber. • No transition effect. • Increasing spectral density = Increased localisability. • F.I. dependant on poor stimuli localisability. • Future: • F.I. with Grouping cues??

  5. Task 2.2 Learning non-individualised HRTFs Cone-of-confusion MVP HRTFs Individual HRTFs

  6. Type – I (2 listeners) Type - II (3 listeners) Task 2.2 Learning non-individualised HRTFs: Results • Response bias significantly determines reversal type = No reversal predisposition. = Majority of front-to-back reversals.

  7. Task 2.3 Complex Smoothing Room Impulse Response (RIR): time domain frequency domain Original RIR Smoothed RIR

  8. Start with a “smoothed” room response Use smoothing based on perception variable spectral resolution variable frequency-dependent windowing Employ “room masking models” perceptual smoothing profiles

  9. Task 2.3 Inverse filtering using smoothed filters time domain frequency domain modification compensation from:“Results for Room Acoustics Equalisation Based on Smoothed Responses”Panagiotis D. Hatziantoniou and John N. Mourjopoulos,114th AES Convention, Amsterdam, March 2003

  10. Task 2.3 Smoothed filters physical metrics Tests in 6 rooms of Volume 60m3 – 11000m3 • EDT reduced by up to 0,5 sec • C80 improves by up to 5 dB • D50 improves by up to 20% • Spectral deviation is reduced up to 4 dB from:“Results for Room Acoustics Equalisation Based on Smoothed Responses”Panagiotis D. Hatziantoniou and John N. Mourjopoulos, 114th AES Convention, Amsterdam, March 2003

  11. Task 2.3 Perceptual factors in room responses • Real-time perception test. • Various stimuli types (steady-state & transients). • Assess multiple perceptual factors.

  12. Task 2.3 Perceptual factors in room responses • Source width. • Source distance. • Envelopment.

  13. Task 2.3 Perceptual factors in room responses • Anchor end-points with illustrative demonstrations and explanation. • Results subjected to factor analysis

  14. Future work • Perceptual factors in room responses (2.3). • ITD/ILD plausibility cues (2.1, 2.2). • The combination of the cues is still debated. • Use F0 grouping with FI for hierarchy of cues (2.2).

  15. AudioGroup, WCL Department of Electrical and Computer Engineering University of Patras, Greece http://www.wcl.ee.upatras.gr/AudioGroup/

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